Comprehension-First Pedagogy and Adaptive, Intrinsically Motivated Tutorials

Greg L. Nelson
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引用次数: 4

Abstract

Two large multinational studies show more than 60% of students incorrectly answer questions about the execution of basic programs. How can we improve program comprehension learning outcomes, and does that improve program writing learning outcomes? Nearly all prior tools and approaches have been evaluated in a writing-focused pedagogical context. People receive instruction on a programming construct's syntax and semantics, practice by writing code, then advance to the next construct (roughly a spiral syntax approach). In contrast, little work has explored a comprehension-first pedagogy, teaching and assessing program semantics - how static code causes dynamic computer behavior - before teaching learners to write code. I hypothesize this pedagogy improves program comprehension and writing learning outcomes, and that an adaptive curriculum of programs that aligns with the learner's interests and assessed knowledge further improves outcomes. Towards that goal, I built and evaluated a comprehension-first tutorial (PLTutor) with a fixed, non-adaptive curriculum, showing 60% higher learning gains (3.9 vs 2.4 on the SCS1) than the writing-focused tutorial Codecademy. I'm looking for new ideas (such as more social (theories, design, etc)), prior work, or methods to inform my thesis proposal and committee selection.
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理解优先教学法与适应性、内在动机性辅导
两项大型跨国研究表明,超过60%的学生错误地回答了有关基本程序执行的问题。我们如何提高程序理解的学习效果,这是否能提高程序编写的学习效果?几乎所有先前的工具和方法都在以写作为重点的教学环境中进行了评估。人们接受关于编程结构的语法和语义的指导,通过编写代码进行练习,然后进入下一个结构(大致是螺旋语法方法)。相比之下,很少有研究探索理解优先的教学法,在教学习者写代码之前,教授和评估程序语义——静态代码如何导致动态计算机行为。我假设这种教学法提高了对课程的理解和写作学习成果,而与学习者的兴趣和评估的知识相一致的适应性课程进一步提高了结果。为了实现这一目标,我建立并评估了一个具有固定,非适应性课程的理解第一教程(PLTutor),显示出比以写作为重点的教程Codecademy高60%的学习收益(3.9 vs 2.4)。我正在寻找新的想法(如更多的社会(理论,设计等)),以前的工作,或方法来通知我的论文开题和委员会的选择。
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